Model Comparison

Gemma 2 9B vs DeepSeek-V2.5

DeepSeek-V2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemma 2 9B outperforms in 0 benchmarks, while DeepSeek-V2.5 is better at 4 benchmarks (GSM8k, HumanEval, MATH, MMLU).

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Sat Apr 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 04 2026 • llm-stats.com
Google
Gemma 2 9B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

226.8B diff

DeepSeek-V2.5 has 226.8B more parameters than Gemma 2 9B, making it 2454.1% larger.

Google
Gemma 2 9B
9.2Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
9.2B
Gemma 2 9B
236.0B
DeepSeek-V2.5

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

Google
Gemma 2 9B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Sat Apr 04 2026 • llm-stats.com

License

Usage and distribution terms

Gemma 2 9B is licensed under Gemma, while DeepSeek-V2.5 uses deepseek.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 2 9B

Gemma

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

Gemma 2 9B was released on 2024-06-27, while DeepSeek-V2.5 was released on 2024-05-08.

Gemma 2 9B is 2 months newer than DeepSeek-V2.5.

Gemma 2 9B

Jun 27, 2024

1.8 years ago

1mo newer
DeepSeek-V2.5

May 8, 2024

1.9 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
DeepSeek
Larger context window (8,192 tokens)
Higher GSM8k score (95.1% vs 68.6%)
Higher HumanEval score (89.0% vs 40.2%)
Higher MATH score (74.7% vs 36.6%)
Higher MMLU score (80.4% vs 71.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 9B
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about Gemma 2 9B vs DeepSeek-V2.5

DeepSeek-V2.5 significantly outperforms across most benchmarks. Gemma 2 9B is made by Google and DeepSeek-V2.5 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 2 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%. DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.
Gemma 2 9B supports an unknown number of tokens and DeepSeek-V2.5 supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Gemma vs deepseek). See the full comparison above for benchmark-by-benchmark results.
Gemma 2 9B is developed by Google and DeepSeek-V2.5 is developed by DeepSeek.